An adaptive mutant multi-objective pigeon-inspired optimization for unmanned aerial vehicle target search problem
HUO Meng-zhen
DUAN Hai-bin
Abstract：Unmanned aerial vehicle (UAV) is an indispensable tool for search missions, which can help find targets in critical and complex environments. The search problem of UAVs is a rather intricate multiobjective optimization problem with multiple constraints under complicated conflict environment. Most search algorithms could not meet the requirements of high efficiency and low consumption in combat environment. The target search approach employed in this paper is a decoupling receding horizon approach based on the agent routing and optical sensor tasking. To optimize the parameters of the target search approach, an adaptive mutant multiobjective pigeon-inspired optimization (AMMOPIO) algorithm is pro-posed for agent routing and optical sensor tasking optimization of target search problem. The utilization of adaptive flight mechanism could obtain the distribution of pigeons with applicable diversity and convergence. The mutation mechanism is used to simplify the model of pigeon-inspired optimization (PIO) to improve the search efficiency. The experimental results validate the feasibility and effectiveness of the proposed AMMOPIO algorithm in target search problem.
Keywords：target searchmulti-objective pigeon-inspired optimizationadaptive flight mechanismmutation mecha-nism
Publication Date：2020-03-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 584-591 )